climate change, land use and forests in india: research and institutional framework in the context...
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Climate change, land use and Climate change, land use and forests in India: research and forests in India: research and institutional framework in the institutional framework in the
context of the Indo-US flux context of the Indo-US flux programmeprogramme
R. Sukumar & N.H.RavindranathR. Sukumar & N.H.Ravindranath
Centre for Ecological SciencesCentre for Ecological Sciences
Indian Institute of ScienceIndian Institute of Science
BangaloreBangalore
Obligations under UNFCCCObligations under UNFCCC
Periodic report of greenhouse gas Periodic report of greenhouse gas emissions inventory from all sectors emissions inventory from all sectors including land use sectors such as forests, including land use sectors such as forests, grassland, wetlands, etcgrassland, wetlands, etc
Assess the vulnerability of natural Assess the vulnerability of natural ecosystems and socioeconomic systems to ecosystems and socioeconomic systems to projected climate changeprojected climate change
Report the steps taken to address climate Report the steps taken to address climate change (mitigation, adaptation)change (mitigation, adaptation)
Forests & Climate ChangeForests & Climate Change Forests play a critical role in global carbon Forests play a critical role in global carbon
cyclecycle Forests contribute about 20% of global COForests contribute about 20% of global CO22
emissionsemissions Forest ecosystems are vulnerable to projected Forest ecosystems are vulnerable to projected
climate changeclimate change Likely to have adverse impacts on forest Likely to have adverse impacts on forest
biodiversity and biomass productionbiodiversity and biomass production Thus need to assess impacts and develop Thus need to assess impacts and develop
adaptation strategiesadaptation strategies Forests provide mitigation opportunity to Forests provide mitigation opportunity to
stabilize GHG concentration in the stabilize GHG concentration in the atmosphere, along with significant co-benefitsatmosphere, along with significant co-benefits
Mitigation through forest sector has been a Mitigation through forest sector has been a contentious issue in climate negotiationscontentious issue in climate negotiations
GHG Emissions from forest GHG Emissions from forest sectorsector
Global emissions of carbon = 7 GtCGlobal emissions of carbon = 7 GtC
Emissions from LUCF = 1.6 to 1.7 GtC Emissions from LUCF = 1.6 to 1.7 GtC 1 1
Tropical deforestation = 13 to 15 Mha Tropical deforestation = 13 to 15 Mha
annuallyannually
Land use change is the dominant factor in Land use change is the dominant factor in
tropical countriestropical countries
ESTIMATES OF STOCKS AND FLUXES ESTIMATES OF STOCKS AND FLUXES FROM INDIAN FORESTSFROM INDIAN FORESTS
0
2000
4000
6000
8000
10000
12000
1880
1980
1986
1986
1994
2005
Car
bon
stoc
k (M
tC)
Biomass carbon Soil carbon
(Sources:
1880: Richard and Flint, 1994;
1980-Richard and Flint, 1994;
1986:Ravindranath et al., 1997;
1986:Chhabra and Dadhwal, 2004;
1994:Haripriya, 2003; 2005:FAO, 2005)
(Sources:
1986-Ravindranath et al., 1997;
1986:Chhabra and Dadhwal, 2004;
1990 – ALGAS (ADB)., 1999;
1994:Haripriya, 2003;
1994: NATCOM, 2004)
Estimates of fluxes from Indian Forests
-20
-15
-10
-5
0
5
10
1986 1986 1990 1994 1994
Flux
es in
Mill
ion
tonn
esFig 1: Estimates of C-stock from Indian forests Fig 2: C-flux estimates from Indian forests
GAPS IN C FLUX ESTIMATESGAPS IN C FLUX ESTIMATES
1.1. Estimation of COEstimation of CO22 emissions are based on emissions are based on Different methods Different methods Different sources of dataDifferent sources of data Different C –poolsDifferent C –pools Different years Different years
Thus the estimates are not comparableThus the estimates are not comparableUncertainties are highUncertainties are highPeriodic spatial data, forest-type wise, Periodic spatial data, forest-type wise,
lacking for flux estimateslacking for flux estimates
1.1. C - Inventory process requires information C - Inventory process requires information pertaining to activity data (i.e. land area pertaining to activity data (i.e. land area change statistics) and impact of land use change statistics) and impact of land use change on the C stock dynamics.change on the C stock dynamics.
2.2. C stock dynamics under different land use C stock dynamics under different land use change systems is poorly understood.change systems is poorly understood.
MITIGATION POTENTIAL OF LULUCF MITIGATION POTENTIAL OF LULUCF SECTORSECTOR
17.0%
80.1%
BOREAL
TEMPERATE
TROPICAL
Projections for mitigation potential for the period 1995 to 2050
Brown et al. 1996, 1999; IPCC 2001
60 – 87 Gt C (cumulative)
1.09 – 1.58 Gt C (annual)
Climate change impact studies at IIScClimate change impact studies at IISc
Evaluate and select models to assess climate Evaluate and select models to assess climate impacts on forestsimpacts on forests Regional Climate Model; Regional Climate Model; Vegetation Response Model; Vegetation Response Model;
Assess impacts of climate change on forest Assess impacts of climate change on forest ecosystems at national levelecosystems at national level
Assess impacts on biodiversity and socio-Assess impacts on biodiversity and socio-economic systems through case studieseconomic systems through case studies
Analyze policy implications of climate impactsAnalyze policy implications of climate impacts Strategies for futureStrategies for future
Research; modeling and databaseResearch; modeling and database Adaptation strategiesAdaptation strategies
Impact of Climate Change Impact of Climate Change on Forest Ecosystemson Forest Ecosystems
SELECTION OF VEGETATION SELECTION OF VEGETATION MODELMODEL
Equilibrium models: BIOME 3Equilibrium models: BIOME 3
Dynamic model: HYBRID 4.2Dynamic model: HYBRID 4.2
BIOME3 used due to input data BIOME3 used due to input data limitations for the HYBRID Modellimitations for the HYBRID Model
CLIMATE DATA FOR BIOMESCLIMATE DATA FOR BIOMESModel used:Model used: Hadley Centre Regional Model; Had RM3 Hadley Centre Regional Model; Had RM3
Mean monthly temp. & rainfall, cloud coverMean monthly temp. & rainfall, cloud cover
Scale:Scale: 0.44 x 0.44 degree RCM grid 0.44 x 0.44 degree RCM grid
Scenarios:Scenarios: SRES; A2 and B2 SRES; A2 and B2
Period:Period: 2071-2100 mid period: 20852071-2100 mid period: 2085
Observed Climate data:Observed Climate data: CRU data set for 1901-1995 CRU data set for 1901-1995 from East Anglia (0.5x0.5 degree grid)from East Anglia (0.5x0.5 degree grid)
Projections of seasonal surface air Projections of seasonal surface air temperature for the period 2041-60, based temperature for the period 2041-60, based
on the regional climate model HadRM2.on the regional climate model HadRM2.
Source:
IITM Pune
Natcom
Projections of seasonal precipitation for Projections of seasonal precipitation for the period 2041-60, based on the regional the period 2041-60, based on the regional
climate model HadRM2.climate model HadRM2.
Source:
IITM Pune
Natcom
Potential impact on forest biomes
(B-2 scenario)
Percentage of grids under different forest types Percentage of grids under different forest types undergoing change in A2 and B2 GHG scenariosundergoing change in A2 and B2 GHG scenarios
0
20
40
60
80
100
120 W
este
rn G
hat s
emi-
ever
gree
n
Wes
tern
Gha
t eve
rgre
en f
ores
t
Man
grov
e
Spr
uce
Kha
ir f
ores
t
Deo
dar
Har
dwoo
ds C
onif
ers
mix
Dec
iduo
us f
ores
t
Sal
ai f
ores
t
Mix
ed c
onif
er
Blu
e-Pi
ne(K
ail)
Fir
SC
RU
B
Mis
cella
neou
s fo
rest
Up-
land
Har
dwoo
ds
Chi
r-pi
ne
Tea
k
Sal
Fir
-Spr
uce
Bam
boo
Fore
st
Kha
si p
ine
Dep
tero
carp
us (
Gur
jan)
Hol
long
% g
rids
und
ergo
ing
chan
ge
A2 B2
Climate impacts on NPP; % Forest biome-RCM grids subjected to change in Climate impacts on NPP; % Forest biome-RCM grids subjected to change in NPP under GHG scenario over the current scenario under B2 ScenarioNPP under GHG scenario over the current scenario under B2 Scenario
0 500 1000 1500 2000 2500 3000
NPP Present NPP A2GHG NPP B2GHG
SUMMARY OF IMPACTSSUMMARY OF IMPACTSHad RM3 Model outputs using SRES: A2 Had RM3 Model outputs using SRES: A2
and B2 scenarios & BIOME3 show;and B2 scenarios & BIOME3 show;1.1. Over 85% of forest grids will undergo Over 85% of forest grids will undergo
changes in forest type (similar trend changes in forest type (similar trend using Had RM2)using Had RM2)
2.2. Regional assessment shows;Regional assessment shows;- Higher impact on Savanna biomes, Teak Higher impact on Savanna biomes, Teak
and Sal forests of central and east, and Sal forests of central and east, temperate biomes of Himalayastemperate biomes of Himalayas
- Lower impact on Western ghats and North-Lower impact on Western ghats and North-east; Evergreen biomeseast; Evergreen biomes
3.3. Large (potential) increase in Net Large (potential) increase in Net primary productivityprimary productivity
-- 70% (B2) to 100% (A2)70% (B2) to 100% (A2)
GAPS IN UNDERSTANDINGGAPS IN UNDERSTANDING
CURRENT STATUSCURRENT STATUS Large uncertainty in climate and Large uncertainty in climate and
vegetation response models; vegetation response models; regional climate levelregional climate level equilibrium vegetation modelequilibrium vegetation model
Inadequate or lack of data for the Inadequate or lack of data for the models models
Adaptation not incorporated in impact Adaptation not incorporated in impact modelsmodels
Location of Mudumalai WLSLocation of Mudumalai WLS
Location of the Mudumalai 50 ha Forest Dynamics Plot
Detailed studies on the forest communityOver 50000 individuals from 250+ species monitored
Topography of the Mudumalai Topography of the Mudumalai plotplot
Recruitment and Mortality in the 50 ha Recruitment and Mortality in the 50 ha plotplot
0
2
4
6
8
10
12
14
16
18
Year
% In
div
idu
als
% Mortality
% Recruitment
Dry season fire
Mortality due to various causesMortality due to various causes
0
2
4
6
8
10
12
14
16
18
Year
Mo
rta
lity
rate
(%
) MortFire
MortEle
MortOthers
Canopy trees: Average growth rates per size Canopy trees: Average growth rates per size class during 3 intervalsclass during 3 intervals
0 20 40 60 80 100 120
-20
24
68
10
Dbh (cm)
Ave
rage
gro
wth
(mm
/yr)
Canopy trees: Average growth rates per size class during 3 intervals
1988-19921992-19961996-2000
Basal area changes (m2 /ha)
1988 = 24.4
1992 = 24.8
1996 = 24.7
2000 = 25.9
2004 = 25.5
Basal area changes (m2 /ha)
1988 = 24.4
1992 = 24.8
1996 = 24.7
2000 = 25.9
2004 = 25.5
Carbon stocks probablyincreased to a greater degree becauseof shift from lower wood density tohigher wood density species
Flux programme should ideally complement Flux programme should ideally complement “on the ground” studies on soils and vegetation“on the ground” studies on soils and vegetation
Spatial data on land use, landuse changes & Spatial data on land use, landuse changes &
forests (partly available)forests (partly available) Data on carbon stocks and fluxes under Data on carbon stocks and fluxes under
different land use and landuse change systems different land use and landuse change systems (lacking)(lacking)
Spatial data on soil, water and plant Spatial data on soil, water and plant physiological functions (limited availability)physiological functions (limited availability)
Flux programme should thus network with Flux programme should thus network with institutions in order to extract maximum institutions in order to extract maximum scientific understanding of C dynamics from the scientific understanding of C dynamics from the soil, through vegetation to the atmospheresoil, through vegetation to the atmosphere
SCIENTIFIC DATA NEEDS FOR CLIMATE CHANGESCIENTIFIC DATA NEEDS FOR CLIMATE CHANGEAND LANDUSE AND LANDUSE CHANGE RESEARCHAND LANDUSE AND LANDUSE CHANGE RESEARCH
Networking on InstitutionsNetworking on Institutions
Land use systems – NRSA, IRS, ISRO, Land use systems – NRSA, IRS, ISRO, SAC & FSISAC & FSI
Vegetation carbon flux - IISc, KFRI, Vegetation carbon flux - IISc, KFRI, ICFRE, NHU, BHU, etcICFRE, NHU, BHU, etc
Soil carbon flux – NBSSLUP, ICAR Soil carbon flux – NBSSLUP, ICAR institutes, Agric. Univinstitutes, Agric. Univ
Climate data – IITM, IISc, IMDClimate data – IITM, IISc, IMD Modeling of fluxes – IISc, IITM, IIT, Modeling of fluxes – IISc, IITM, IIT,
National Coordination National Coordination DSTDST Dedicated institution?? Dedicated institution??
Regional lead institutions – Research areaRegional lead institutions – Research area Networking of all institutions Networking of all institutions Funding Funding
DST, MoEF, ICAR, ICFREDST, MoEF, ICAR, ICFRE External fundingExternal fundingLinking with endusers such as – MoEF, ICAR, Linking with endusers such as – MoEF, ICAR,
research institutionsresearch institutions